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Deep learning in the identification of psoriatic skin lesions

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Summary:Psoriasis is a dermatological lesion that manifests in several regions of the body. Its late diagnosis can generate the aggravation of the disease itself, as well as of the comorbidities associated with it. The proposed work presents a computational system for image classification in smartphones, through deep convolutional neural networks, to assist the process of diagnosis of psoriasis. The dataset and the classification algorithms used revealed that the classification of psoriasis lesions was most accurate with unsegmented and unprocessed images, indicating that deep learning networks are able to do a good feature selection. Smaller models have a lower accuracy, although they are more adequate for environments with power and memory restrictions, such as smartphones.
Main Authors:Lima, Gabriel Lenin Silva
Other Authors:Pires, Carolina; Beuren, Arlete Teresinha; Lopes, Rui Pedro
Subject:Image processing Deep learning Psoriasis classification Mobile application
Year:2024
Country:Portugal
Document type:conference paper
Access type:restricted access
Associated institution:Instituto Politécnico de Bragança
Language:English
Origin:Biblioteca Digital do IPB

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